"""Execute the notebook in a fresh CPU kernel, with an 8 GiB address-space cap.""" import argparse import json import os from pathlib import Path import resource import sys import time import nbformat from nbclient import NotebookClient def main(): parser = argparse.ArgumentParser() parser.add_argument("--remote", action="store_true") parser.add_argument("--revision") parser.add_argument("--output", type=Path, default=Path("/tmp/trajectory_eda_executed.ipynb")) args = parser.parse_args() root = Path(__file__).resolve().parents[1] os.environ.update(MPLCONFIGDIR="/tmp/trajectory_mpl", OPENBLAS_NUM_THREADS="1", OMP_NUM_THREADS="1", CUDA_VISIBLE_DEVICES="", HF_HUB_DISABLE_IMPLICIT_TOKEN="1", HF_HOME="/tmp/trajectory_anonymous_hf") os.environ.pop("HF_TOKEN", None) os.environ["CORPUS_EXPORT_DIR"] = "/tmp/trajectory_eda_exports" if args.remote: os.environ.pop("CORPUS_LOCAL_ROOT", None) else: os.environ["CORPUS_LOCAL_ROOT"] = str(root) if args.revision: os.environ["CORPUS_REVISION"] = args.revision resource.setrlimit(resource.RLIMIT_AS, (8 * 1024**3, 8 * 1024**3)) kernel_dir = Path("/tmp/trajectory_jupyter/kernels/trajectory-cpu") kernel_dir.mkdir(parents=True, exist_ok=True) (kernel_dir / "kernel.json").write_text(json.dumps({ "argv":[sys.executable,"-m","ipykernel_launcher","-f","{connection_file}"], "display_name":"Trajectory CPU validation", "language":"python"})) os.environ["JUPYTER_PATH"] = "/tmp/trajectory_jupyter" nb = nbformat.read(root / "trajectory_eda_colab.ipynb", as_version=4) nb.cells.append(nbformat.v4.new_code_cell(""" # Validation-only checks for lazy examples and the interactive callback. process = example_summary.loc[(example_summary.example_kind == 'process') & (example_summary.truncated == True)].iloc[0] assert inspect_example(process.example_id)['metadata']['truncated'] is True packet = example_summary.loc[example_summary.example_kind == 'experiment1_judge_packet'].iloc[0] assert inspect_example(packet.example_id)['packet_id'] == packet.example_id controls['collection'].value = 'olmo' rejected = episodes.loc[(episodes.collection == 'olmo') & (episodes.rejected_responses > 0)].sort_values('events').iloc[0] picker.value = rejected.episode_id canonical_only.value = False only_rejected.value = True show_timeline() assert selected_bundle['episode']['episode_id'] == rejected.episode_id assert any(e['rejected_response'] for e in selected_bundle['events']) controls['collection'].value = 'qwen' assert all(eid in set(episodes.loc[episodes.collection == 'qwen','episode_id']) for label,eid in picker.options) print('Inspector filters, rejected-response callback, truncated example, and packet loads passed.') """)) start = time.monotonic() client = NotebookClient(nb, timeout=240, kernel_name="trajectory-cpu", resources={"metadata":{"path":"/tmp"}}) client.execute() nbformat.write(nb, args.output) report = {"status":"passed", "mode":"anonymous_remote" if args.remote else "local_publication_copy", "code_cells_executed":sum(c.cell_type == "code" for c in nb.cells), "elapsed_seconds":round(time.monotonic()-start,2), "address_space_cap_gib":8, "peak_child_rss_mib":round(resource.getrusage(resource.RUSAGE_CHILDREN).ru_maxrss/1024,2), "gpu_visible":False, "model_calls":0, "login_required":False, "dataset_revision":args.revision or "resolved_inside_notebook", "executed_notebook":str(args.output)} target = root / "provenance" / ("notebook_anonymous_execution.json" if args.remote else "notebook_cpu_execution.json") target.write_text(json.dumps(report,indent=2)+"\n") print(json.dumps(report,indent=2)) if __name__ == "__main__": main()